In order to improve efficiency of ammonia synthesis using the Haber–Bosch (HB) process with Fe-based catalysts, we employed quantum mechanics (QM)-based hierarchical high-throughput catalyst screening (HHTCS) of 49 possible metal dopants. Here, we consider the Fe(211) surface (one of the two most active iron catalyst facets) to identify dopants that dramatically increase the turnover frequency (TOF) for HB synthesis. We found that under HB conditions, this surface reconstructs to form the Fe(211)R missing-row surface. Focusing on dopants with a strong preference for the subsurface site, we found that Co is the most promising candidate among the 49. We then examined the full reaction pathway on this Co-doped Fe(211)R surface, considering all 19 important 2 × 2 configurations and calculated the free-energy barriers (ΔG∫) for all 12 important reaction steps. At 673 K and 20 atm, we find a decrease, δ(ΔG∫) = −0.19 eV, in the overall reaction free-energy barrier for the Co-doped case. We then carried out kinetic Monte Carlo simulations for 60–120 min using 100 replicas with the full reaction path using rates from QM free-energy reaction barriers to predict that the TOF for the Co-doped surface increases by a factor of 2.8 with respect to the undoped Fe(211)R surface. Thus, the Co-doped Fe(211)R system could lower the extreme HB pressure of 200 atm to ∼40 atm at 773 K while maintaining the same TOF as that of undoped Fe(211)R. We conclude that Co dopants in the Fe catalyst could significantly improve the catalytic efficiency of ammonia synthesis under industrial conditions. This excellent performance of the Co-doped system is explained in terms of a surface spin analysis on the N₂-bonded configurations that show how Co dopants shift the N₂ surface-binding mode. This demonstrates that metal surface spins can be used as quantitative descriptors to understand reaction energetics. This study demonstrates that the HHTCS kinetic analysis of the free-energy reaction path in terms of essential configurations can enable discovery of the salient barriers to overcome and best dopant candidates for further improvements
